Problem-Based SRS: método para especificação de requisitos de software baseado em problemas

Requirements specification has long been recognized as critical activity in software development processes because of its impact on project risks when poorly performed. A large amount of studies addresses theoretical aspects, propositions of techniques, and recommended practices for Requirements Engineering (RE). To be successful, RE have to ensure that the specified requirements are complete and correct what means that all intents of the stakeholders in a given business context are covered by the requirements and that no unnecessary requirement was introduced. However, the accurate capture the business intents of the stakeholders remains a challenge and it is a major factor of software project failures. This master’s dissertation presents a novel method referred to as “Problem-Based SRS” aiming at improving the quality of the Software Requirements Specification (SRS) in the sense that the stated requirements provide suitable answers to real customer ́s businesses issues. In this approach, the knowledge about the software requirements is constructed from the knowledge about the customer ́s problems. Problem-Based SRS consists in an organization of activities and outcome objects through a process that contains five main steps. It aims at supporting the software requirements engineering team to systematically analyze the business context and specify the software requirements, taking also into account a first glance and vision of the software. The quality aspects of the specifications are evaluated using traceability techniques and axiomatic design principles. The cases studies conducted and presented in this document point out that the proposed method can contribute significantly to improve the software requirements specification.

Illness cognitions and coping self-efficacy in depression among persons with low vision

PURPOSE: To investigate the mediating role of coping self-efficacy (CSE) between two types of illness cognitions (i.e., acceptance and helplessness) and depressive symptoms in persons with low vision.

METHODS: This was a single-group, cross-sectional study. Patients with visual acuity < 6/12 in the better eye and at least minimal depressive symptoms (≥5 on the Patient Health Questionnaire-9 [PHQ-9]) were recruited from vision rehabilitation services and participated in telephone-administered structured interviews at one time point. Measures were the PHQ-9, CSE Scale, and Illness Cognition Questionnaire. Structural equation modeling (SEM) devised the causal flow of illness cognitions and their observed indirect effects on depressive symptoms via the CSE mediators: problem focused, emotion focused, and social support.

RESULTS: The study comprised 163 patients (mean age 62 years; 61% female), most with age-related macular degeneration (26%) and moderate vision impairment (44%, <6/18-6/60). Structural equation modeling indices indicated a perfect fit (χ2 < 0.001, P = 1.00), accounting for 55% of the variance in depressive symptoms. Lower levels of acceptance and higher levels of helplessness illness cognitions were associated with lower self-efficacy in problem-focused coping (β = 0.38, P < 0.001, β = -0.28, P < 0.01, respectively), which in turn was associated with greater depressive symptom severity (β = -0.54, P < 0.001).

CONCLUSIONS: Lack of acceptance and greater helplessness relating to low vision led to a lack of perceived capability to engage in problem-focused coping, which in turn promoted depressive symptoms. Third-wave cognitive-behavioral treatments that focus on acceptance may be efficacious in this population.

An Efficient and Verifiable Solution to the Millionaire Problem

A new solution to the millionaire problem is designed on the base of two new techniques: zero test and batch equation. Zero test is a technique used to test whether one or more ciphertext contains a zero without revealing other information. Batch equation is a technique used to test equality of multiple integers. Combination of these two techniques produces the only known solution to the millionaire problem that is correct, private, publicly verifiable and efficient at the same time.